As represented by words such as big data, the present age is full of data. In information science, knowing how to analyze huge data and how to handle becomes one of the most important problems to be solved. Big data has many problems that need a complex analysis. For example, when a certain result is obtained, it may be desired to find cause of the result. This is referred to as an inverse problem. It becomes difficult to find the cause as a phenomenon becomes more complicated, and in general, efficient algorithm for obtaining an initial value from a result is not present. In the worst case, the exhaustive search should be conducted for the initial value. This is one of the difficult problems in big data. Alternatively, there are also many problems to select an optimal solution from among many choices on the basis of big data. Also, in this case, when all possibilities are taken into account, a need for the exhaustive search comes out. From this background, a computer which efficiently solves a problem which needs the exhaustive search is needed.
On the exhaustive search problem, expectations for a quantum computer are large. The quantum computer simultaneously realizes “0” and “1”, each of which is composed of a basic element called a quantum bit. For that reason, the quantum computer has a potential to simultaneously calculate all solution candidates as the initial value and certainly realize the exhaustive search. However, the quantum computer needs to maintain quantum coherence over the entire calculation time and there appears no prospect that this is realized.
In this situation, a method that has come to be noted is called adiabatic quantum computing (NPL 1). This method is one in which a problem is converted such that a ground state of a certain physical system becomes a solution and the solution is obtained by finding the ground state. The Hamiltonian of a physical system for which a problem is set is assumed as H^p. However, the Hamiltonian is not assumed as H^p at a time point of starting computation and is assumed as another Hamiltonian H^0 with which a ground state is prepared easily and clearly, apart from H^D. Next, the Hamiltonian is allowed to transition from H^0 to H^p by spending enough time. When enough time is spent, a system remains in the ground state and a ground state of the Hamiltonian H^p is obtained. This is the principle of adiabatic quantum computing. When a calculation time is assumed as τ, the Hamiltonian becomes Equation (1).
                                          H            ^                    ⁡                      (            t            )                          =                                            (                              1                -                                  t                  τ                                            )                        ⁢                                          H                ^                            0                                +                                    t              τ                        ⁢                                          H                ^                            p                                                          [                  Equation          ⁢                                          ⁢          1                ]            
The solution which is time-evolved is obtained based on the Schrodinger equation of Equation (2).
                              i          ⁢                                          ⁢          ℏ          ⁢                                    ∂                                                                                  ∂              t                                ⁢                                                ψ              ⁡                              (                t                )                                      〉                          =                                            H              ^                        ⁡                          (              t              )                                ⁢                                                ψ              ⁡                              (                t                )                                      〉                                              [                  Equation          ⁢                                          ⁢          2                ]            
The adiabatic quantum computing is also applicable to the problem that needs the exhaustive search and reaches the solution in a unidirectional process. However, when a calculation process needs to follow the Schrodinger equation of Equation (2), it is necessary to maintain quantum coherence similar to the quantum computer. However, the quantum computer repeats a gate operation for 1 quantum bit or between 2 quantum bits, whereas adiabatic quantum computing is for simultaneously interacting over the entirety of a quantum bit system and the way of thinking for coherence is different. For example, the gate operation to a certain quantum bit is considered. At this time, if there is interaction between the quantum bit and other quantum bits, interaction is cause of decoherence, but in adiabatic quantum computing, all quantum bits are allowed to simultaneously interact and thus, decoherence is not caused in a case such as this example. Adiabatic quantum computing in which this difference is reflected is thought to be robust to decoherence as compared with the quantum computer.
However, there is also a problem to be solved in adiabatic quantum computing. Even though adiabatic quantum computing becomes more robust with respect to decoherence compared to the quantum computer, if a computation process follows the Schrodinger equation of Equation (2), sufficient coherence is needed as well. Matters that a system implement adiabatic quantum computing is a superconducting magnetic flux quantum bit system are a problem to be solved (PTL 1 and NPL 2). This is because in a case of using superconductivity, a cryogenic cooling device is needed. Matters that an extremely low temperature is needed are the problem to be solved for realizing a practical computer.